Friday, November 21, 2014

This map shows the happiness of countries around the world. It shows the extent to which countries deliver long, happy and environmentally sustainable lives for their citizens according to the Happy Planet Index HPI

An interesting map from MoveHub reveals how happy people are around the world.

The new HPI results show the extent to which 151 countries across the globe produce long, happy and sustainable lives for the people that live in them. The overall index scores rank countries based on their efficiency, how many long and happy lives each produces per unit of environmental output.

Each of the three component measures – life expectancy, experienced well-being and Ecological Footprint – is given a traffic-light score based on thresholds for good (green), middling (amber) and bad (red) performance. These scores are combined to an expanded six-colour traffic light for the overall HPI score, where, to achieve bright green – the best of the six colours, a country would have to perform well on all three individual components.

The scores for the HPI and the component measures can be viewed in map or table-form. By clicking on any individual country in the map or table you can explore its results in more detail.

Most measures of national progress put a high emphasis on the economic activity without too much concern for environmental limits or less tangible aspects, such as well-being. The HPI (Happy Planet Index) puts at the heart the idea that happiness is not necessarily about wealth, but living long lives with a high experience of well-being within the environmental limits of the planet.

The reason for some high-income nations to score significantly below other nations is the ecological footprint left on the planet. It is important to note, however, that the data does not take into account internal inequality measures and human rights issues tied to some countries which are high up in the rankings. Similarly, this map illustrates the differences in the absolute HPI score and does not take into account the differences between the variables that determine the score.